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Virtual Reality (ICVR), IEEE International Conference on

作者： Fardani Annisa Damastuti Kenan Firmansyah Yunifa Miftachul Arif Ali Ridho Barakbah Mochamad Hariadi Department of Electrical Engineering Institut Teknologi Sepuluh Nopember Surabaya Indonesia Department of Creative Multimedia Technology Electronic Engineering Polytechnic Institute of Surabaya Surabaya Indonesia Department of Informatics Engineering Universitas Islam Negeri Maulana Malik Ibrahim Malang Indonesia Department of Informatics and Computer Engineering Electronic Engineering Polytechnic Institute of Surabaya Surabaya Indonesia Department of Computer Engineering Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350364231

ISBN: (纸本)9798350364248

The immersive nature of virtual reality (VR) gaming is significantly improved by the implementation of dynamic environmental systems. This paper focuses on the development and impact of a dynamic day and night cycle in a serious VR game. This feature is intended to simulate a full 24-hour cycle within a 10-minute gameplay session, resulting in a seamless transition between different times of day that impacts both the visual aesthetics and gameplay mechanics. The day and night cycle introduces strategic depth by requiring players to adjust their management strategies according to the time of day, which affects resource availability, operational efficiency, and conditions. This system not only enhances visual fidelity but also directly impacts gameplay, necessitating that player modify their strategies in response to the changing environment. Visual aesthetics are expected to increase by 15%, strategic profundity will be improved by 20%, and player immersion will be enhanced by 25%, according to the research findings. This investigation underscores the importance of natural cycles in enhancing the strategic complexity, interactivity, and realism of virtual reality environments, thereby offering valuable insights for the creation of future virtual reality games.

关键词： Visualization Accuracy Virtual reality Games Immersive experience Hardware Complexity theory

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Awake at the Wheel: Enhancing Automotive Safety through EEG-Based Fatigue Detection

arXiv

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arXiv 2024年

作者： Siddhad, Gourav Dey, Sayantan Roy, Partha Pratim Iwamura, Masakazu Department of Computer Science and Engineering Indian Institute of Technology Uttarakhand Roorkee247667 India Department of Core Informatics Graduate School of Informatics Osaka Metropolitan University Sakai Osaka599-8531 Japan

Driver fatigue detection is increasingly recognized as critical for enhancing road safety. This study introduces a method for detecting driver fatigue using the SEED-VIG dataset, a well-established benchmark in EEG-based vigilance analysis. By employing advanced pattern recognition technologies, including machine learning and deep neural networks, EEG signals are meticulously analyzed to discern patterns indicative of fatigue. This methodology combines feature extraction with a classification framework to improve the accuracy of fatigue detection. The proposed NLMDA-Net reached an impressive accuracy of 83.71% in detecting fatigue from EEG signals by incorporating two novel attention modules designed specifically for EEG signals, the channel and depth attention modules. NLMDA-Net effectively integrate features from multiple dimensions, resulting in improved classification performance. This success stems from integrating temporal convolutions and attention mechanisms, which effectively interpret EEG data. Designed to capture both temporal and spatial characteristics of EEG signals, deep learning classifiers have proven superior to traditional methods. The results of this study reveal a substantial enhancement in detection rates over existing models, highlighting the efficacy of the proposed approach for practical applications. The implications of this research are profound, extending beyond academic realms to inform the development of more sophisticated driver assistance systems. Incorporating this fatigue detection algorithm into these systems could significantly reduce fatigue-related incidents on the road, thus fostering safer driving conditions. This paper provides an exhaustive analysis of the dataset, methods employed, results obtained, and the potential real-world applications of the findings, aiming to contribute significantly to advancements in automotive safety. Copyright © 2024, The Authors. All rights reserved.

关键词： Deep neural networks

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Enhancing EEG Signal-Based Emotion Recognition with Synthetic Data: Diffusion Model Approach

arXiv

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arXiv 2024年

作者： Siddhad, Gourav Iwamura, Masakazu Roy, Partha Pratim Department of Computer Science and Engineering Indian Institute of Technology Uttarakhand Roorkee247667 India Department of Core Informatics Graduate School of Informatics Osaka Metropolitan University Sakai Osaka599-8531 Japan

Emotions are crucial in human life, influencing perceptions, relationships, behaviour, and choices. Emotion recognition using Electroencephalography (EEG) in the Brain-computer Interface (BCI) domain presents significant challenges, particularly the need for extensive datasets. This study aims to generate synthetic EEG samples that are similar to real samples but are distinct by augmenting noise to a conditional denoising diffusion probabilistic model, thus addressing the prevalent issue of data scarcity in EEG research. The proposed method is tested on the DEAP dataset, showcasing upto 4.21% improvement in classification performance when using synthetic data. This is higher compared to the traditional GAN-based and DDPM-based approaches. The proposed diffusion-based approach for EEG data generation appears promising in refining the accuracy of emotion recognition systems and marks a notable contribution to EEG-based emotion recognition. Our research further evaluates the effectiveness of state-of-the-art classifiers on EEG data, employing both real and synthetic data with varying noise levels. © 2024, CC BY.

关键词： Emotion Recognition

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The Impact Of Social Media On The academic Development Of School Students 10

The Impact Of Social Media On The Academic Development Of Sc...

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10th IEEE Region 10 Humanitarian technology Conference, R10-HTC 2022

作者： Perera, U.D.Harshi Lahiruka Harshanath, S.M.B. Sri Lanka Institute of Information Technology Faculty of Graduate Studies Research Sri Lanka Sliit Department of Computer Science and Software Engineering Sri Lanka

ISBN: (数字)9781665401562

ISBN: (纸本)9781665401562

While social media has reached the peak of its popularity, the addiction to social media become a major issue. With the present pandemic the authorities are forced to close the schools and to shift to virtual classrooms. The students must therefore use a connected devise to participate to the classes which has contributed to the increased addiction to social media among the youth. Inappropriate or excessive usage social media may affect the studies as well as mental and physical health of the user. Spread of fake news through social media has also been a big problem. Mainly, due to its convenience of usage, social media, has become a daily necessity, especially among the youth. So, the primary goal of this study project is to determine the impact of social media on school students' academic performance and to suggest a separate social media platform which will meet their needs. © 2022 IEEE.

关键词： Students

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Alapana Generation using Finite State Machines and Generative Adversarial Networks

Alapana Generation using Finite State Machines and Generativ...

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International research Conference on Smart Computing and Systems engineering (SCSE)

作者： Vithushigan Jayatharan Dileeka Alwis Computer Science and Engineering University of Westminster London UK Department of Computing Informatics Institute of Technology Colombo Sri Lanka

The recent advancements in deep learning techniques and computational power have promoted the development of novel approaches for music generation. In this study, generating alapana, an improvisational form of Carnatic music was proposed, by leveraging Generative Adversarial Networks (GANs) and Finite State Machines (FSM). The goal is to create melodious alapana sequences that follow a given input Raga, ensuring continuity and coherence throughout the generated musical piece. The proposed approach incorporates Carnatic music theory rules into the generation process to enhance the structural coherence of the generated alapana. Additionally, various hyperparameter settings were explored to achieve the best performance. The Fréchet Audio Distance, Percentage of Correct Pitches and the Subjective evaluation through human listeners are the evaluation metrics of this approach. The result of this study demonstrates the potential of using GANs and FSM for generating continuous and pleasing alapana sequences in Carnatic music, contributing to the growing body of research in computational music generation.

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Digital Twins and Intelligent IoT for a Better World (Panel Discussion Report-I of IEEE AIoTSys2023)

Digital Twins and Intelligent IoT for a Better World (Panel ...

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2023 International Conference on Artificial Intelligence of Things and Systems, AIoTSys 2023

作者： Huang, Runhe Zhang, Daqing Yu, Zhiwen Nugent, Chris Jia, Weijia Yang, Kun Zhang, Yan Sekimoto, Yoshihide Guo, Bin Faculty of Computer and Information Sciences Hosei University Tokyo Japan Peking University Ip Paris France Harbin Engineering University Northwestern Polytechnical University China School of Computing Ulster University Ireland BNU-UIC Joint Ai Research Institute Beijing Normal University China School of Computer Science and Electronic Engineering University of Essex United Kingdom Department of Informatics University of Oslo Norway Institute of Industrial Science University of Tokyo Japan School of Computer Science Northwestern Polytechnical University China

ISBN: (纸本)9798350312270

This position paper provides a summary report of the panel discussion on "Digital Twins and Intelligent IoT for a Better World"at the International Conference on Artificial Intelligence of Things and Systems (AIoTSys'23). The panel featured seven distinguished invited panelists, including four IEEE Fellows from Peking University, Beijing Normal University, University of Essex, and the University of Oslo. Additionally, there was one vice president from Harbin engineering University, one school head from Ulster University, and one center vice director from the University of Tokyo. The panel covered seven topics: (1) The cost-effectiveness of IoTenabled digital twin design, (2) Ubiquitous crowd computing systems, (3) The vision for the fusion of the Intelligent IoT with the Digital Twin, (4) Intelligent networking in relation to Chinese culture and education, (5) Data-driven digital twin wireless networks, (6) Digital twins edge networking, and (7) The automatic generation of urban digital twins from local government s open data. The panel generated lively and comprehensive discussions, and this report represents the enriched outcome of our panelists insights, visions, and the interactive discussions with the audience. © 2023 IEEE.

关键词： Internet of things

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Apply Combined Model Between VGG16 and LightGBM on Weather Image Recognition

Apply Combined Model Between VGG16 and LightGBM on Weather I...

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IEEE International Conference on research, Innovation and Vision for the Future

作者： Tran Quy Nam Irfan Syamsuddin Posts and Telecommunications Institute of Technology Hanoi Vietnam Department of Informatics & Computer Engineering Politeknik Negeri Ujung Pandang Indonesia

This research implements hybrid deep learning network models for weather image classification. The study proposes to apply a combined model, namely VGG16-LightGBM. In its architecture model, a pre-train convolutional neural network (CNN) name as VGG16 is employed for feature extraction of images and the LightGBM algorithm is used to make classification. The results on accuracy of proposed models were compared with four other models, namely Xception, Inception V3,Vgg19, Vgg16 which are all implemented by transfer learning mechanism on the same dataset. The experimental results proved that the VGG16-LightGBM gives the best performance with the highest accuracy of 81,28%, outperforms the transfer learning technique of other 4 pre-train models in the problem of weather image classification.

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An Explainable Artificial Intelligence model in the assessment of Brain MRI Lesions in Multiple Sclerosis using Amplitude Modulation – Frequency Modulation multi-scale feature sets

An Explainable Artificial Intelligence model in the assessme...

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International Conference on Digital Signal Processing (DSP)

作者： Andria Nicolaou Antonis Kakas Constantinos S. Pattichis Marios S. Pattichis Kevin Fotso Christos P. Loizou Marios Pantzaris Department of Computer Science University of Cyprus Nicosia Cyprus Department of Electrical Engineering and Computer Engineering University of New Mexico USA Department of Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus Cyprus Institute of Neurology and Genetics Nicosia Cyprus

The objective of this study was to implement an explainable artificial intelligence (AI) model with embedded rules to assess Multiple Sclerosis (MS) disease evolution based on brain Magnetic Resonance Imaging (MRI) multi-scale lesion evaluation. Amplitude Modulation-Frequency Modulation (AM-FM) features were extracted from manually segmented brain MS lesions obtained using MRI and were labeled with the Expanded Disability Status Scale (EDSS). Machine learning models were used to classify the MS subjects with a benign course of the disease and subjects with advanced accumulating disability. Rules were extracted from the selected model with high accuracy and then were modified to perform argumentation-based reasoning. It is demonstrated that the proposed explainable AI modeling can distinguish MS subjects and give meaningful information to track the progression of the disease. Future research will examine more subjects and add new feature sets and models.

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Examine the Impact of Visual Content when Used in Mixed Media Applications 15

Examine the Impact of Visual Content when Used in Mixed Medi...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Rajiv Gandhi, N. Goyal, Shitij Pattanaik, Ashutosh Tamkhade, Jayashree Kuppuraj, T. Pandey, Noopor Prince Shri Venkateshwara Padmavathy Engineering College Department of Civil Engineering Chennai127 India Quantum University Research Center Quantum University India School of Engineering and Technology Mechaical Engineering Karnataka Bangalore India E&TC Vishwakarma Institute of Information Technology Pune India Karpagam Academy of Higher Education Department of Computer Applications Coimbatore641 021 India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India

ISBN: (纸本)9798350370249

Visible content in mixed media programs may have a large effect on its customers. By combining both visible and auditory elements, it permits users to have an extra immersive revel in terms of eating the content. Visible content material consisting of pics, films, diagrams, and so forth. It can all be used to in addition enhance enjoyment while used as a complement or number one source of records. Visuals can simplify complicated ideas and provide a less complicated way to navigate through products or services. It may be specifically useful in academic contexts. Moreover, visible content material can be used to increase Engagement via telling a story or thrillingly providing information. It helps create a connection between the consumer and the content material and makes the revel extra memorable. In the end, visuals can encourage user interplay with interactive elements along with buttons, menus, and bureaucracy, all of which can decorate the user experience. The use of visual content in combined media applications may have a full-size effect on the person's enjoyment. Through the incorporation of visuals, customers can benefit from a higher knowledge of the context and cause of the utility, in addition to an immersive experience that similarly complements the content material offered. © 2024 IEEE.

关键词： FORTH (programming language)

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Single photon flux imaging with sub-pixel resolution by motion compensation 17

Single photon flux imaging with sub-pixel resolution by moti...

引用

Advanced Photon Counting Techniques XVII 2023

作者： Laurenzis, Martin Bacher, Emmanuel Seets, Trevor Ingle, Atul Velten, Andreas Christnacher, Frank French-German Research Institute of Saint-Louis 5 Rue du General Cassagnou Saint-Louis68301 France Department of Electrical and Computer Engineering University of Wisconsin-Madison MadisonWI53706 United States Department of Computer Science Portland State University PortlandOR97201 United States Department of Biostatistics and Medical Informatics University of Wisconsin-Madison MadisonWI53706 United States

ISBN: (纸本)9781510661387

Single photon counting avalanche diodes (SPADs) are versatile sensors for active and time-correlated measurements such as ranging and fluorescence imaging. These detectors also have great potential for passive or uncorrelated imaging. Recently, it was demonstrated that passive imaging of photon flux is possible by determining the mean photon arrival time. For ambient light illumination, timestamp data can be interpreted as a metric for the photon impingement rate. Various applications have been investigated including high-dynamic-range imaging, single-photon imaging, and capture of fast-moving objects or dynamic scenes. However, the appearance of noise and motion blur requires sophisticated signal processing that enables sub-pixel resolution imaging and reconstruction of the scene by motion compensation. In this paper, we present new results on the evaluation of global scene motion. In our approach, motion is intentionally generated by a rotating wedge prism, resulting in continuous global motion on a circular path. We have studied scenes with different optical contrast. © 2023 SPIE.

关键词： Avalanche diodes

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